Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/124129
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Type: Journal article
Title: On the probability of strain invasion in endemic settings: accounting for individual heterogeneity and control in multi-strain dynamics
Author: Meehan, M.T.
Cope, R.C.
McBryde, E.S.
Citation: Journal of Theoretical Biology, 2020; 487
Publisher: Elsevier
Issue Date: 2020
ISSN: 0022-5193
1095-8541
Statement of
Responsibility: 
Michael T. Meehan, Robert C. Cope, Emma S. McBryde
Abstract: Pathogen evolution is an imminent threat to global health that has warranted, and duly received, considerable attention within the medical, microbiological and modelling communities. Outbreaks of new pathogens are often ignited by the emergence and transmission of mutant variants descended from wild-type strains circulating in the community. In this work we investigate the stochastic dynamics of the emergence of a novel disease strain, introduced into a population in which it must compete with an existing endemic strain. In analogy with past work on single-strain epidemic outbreaks, we apply a branching process approximation to calculate the probability that the new strain becomes established. As expected, a critical determinant of the survival prospects of any invading strain is the magnitude of its reproduction number relative to that of the background endemic strain. Whilst in most circumstances this ratio must exceed unity in order for invasion to be viable, we show that differential control scenarios can lead to less-fit novel strains invading populations hosting a fitter endemic one. This analysis and the accompanying findings will inform our understanding of the mechanisms that have led to past instances of successful strain invasion, and provide valuable lessons for thwarting future drug-resistant strain incursions.
Keywords: Anti-microbial drug resistance; Branching process; Epidemic control; Multi-strain; Pathogen evolution; Strain invasion
Rights: © 2019 Elsevier Ltd. All rights reserved.
RMID: 1000012950
DOI: 10.1016/j.jtbi.2019.110109
Grant ID: http://purl.org/au-research/grants/arc/CE14010 0 049
Appears in Collections:Mathematical Sciences publications

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